ECON 6550 - Econometrics

Credits: (3)
Typically Taught Fall Semester: Full Sem
Description: Regression Analysis. Topics include ordinary least squares, dummy variables, autocorrelation, heteroskedasticity, and serial correlation. Computers used extensively. By the end of the course, students will be able to: Develop a multiple regression model, understand the assumptions of multiple regression and recognize the consequences when they are not satisfied, test for statistical significance in a multiple regression setting, use dummy variables as independent and dependent variables, recognize endogenous regressors, and simulate key econometric principles.
Pre-requisite(s): Admission to the Master of Science in Data Science and the leveling courses associated with those requirements.